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      MTDH-stabilized DDX17 promotes tumor initiation and progression through interacting with YB1 to induce EGFR transcription in Hepatocellular Carcinoma

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          Abstract

          Metadherin (MTDH) is a well-established oncogene in various cancers including Hepatocellular Carcinoma (HCC). However, the precise mechanism through which MTDH promotes cancer-related signaling pathways in HCC remains unknown. In this study, we identified DDX17 as a novel binding partner of MTDH. Furthermore, MTDH increased the protein level of DDX17 by inhibiting its ubiquitination. We confirmed that DDX17 was a novel oncogene, with dramatically upregulated expression in HCC tissues. The increased expression of DDX17 was closely associated with vascular invasion, TNM stage, BCLC stage, and poor prognosis. In vitro and in vivo tests demonstrated that DDX17, a downstream target of MTDH, played a crucial role in tumor initiation and progression. Mechanistically, DDX17 acted as a transcriptional regulator that interacted with Y-box binding protein 1 (YB1) in the nucleus, which in turn drove the binding of YB1 to its target epidermal growth factor receptor (EGFR) gene promoter to increase its transcription. This in turn increased expression of EGFR and the activation of the downstream MEK/pERK signaling pathway. Our results identify DDX17, stabilized by MTDH, as a powerful oncogene in HCC and suggest that the DDX17/YB1/EGFR axis contributes to tumorigenesis and metastasis of HCC.

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          Most cited references42

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          Hallmarks of Cancer: The Next Generation

          The hallmarks of cancer comprise six biological capabilities acquired during the multistep development of human tumors. The hallmarks constitute an organizing principle for rationalizing the complexities of neoplastic disease. They include sustaining proliferative signaling, evading growth suppressors, resisting cell death, enabling replicative immortality, inducing angiogenesis, and activating invasion and metastasis. Underlying these hallmarks are genome instability, which generates the genetic diversity that expedites their acquisition, and inflammation, which fosters multiple hallmark functions. Conceptual progress in the last decade has added two emerging hallmarks of potential generality to this list-reprogramming of energy metabolism and evading immune destruction. In addition to cancer cells, tumors exhibit another dimension of complexity: they contain a repertoire of recruited, ostensibly normal cells that contribute to the acquisition of hallmark traits by creating the "tumor microenvironment." Recognition of the widespread applicability of these concepts will increasingly affect the development of new means to treat human cancer. Copyright © 2011 Elsevier Inc. All rights reserved.
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            Emerging functions of the EGFR in cancer

            The physiological function of the epidermal growth factor receptor (EGFR) is to regulate epithelial tissue development and homeostasis. In pathological settings, mostly in lung and breast cancer and in glioblastoma, the EGFR is a driver of tumorigenesis. Inappropriate activation of the EGFR in cancer mainly results from amplification and point mutations at the genomic locus, but transcriptional upregulation or ligand overproduction due to autocrine/paracrine mechanisms has also been described. Moreover, the EGFR is increasingly recognized as a biomarker of resistance in tumors, as its amplification or secondary mutations have been found to arise under drug pressure. This evidence, in addition to the prominent function that this receptor plays in normal epithelia, has prompted intense investigations into the role of the EGFR both at physiological and at pathological level. Despite the large body of knowledge obtained over the last two decades, previously unrecognized (herein defined as ‘noncanonical’) functions of the EGFR are currently emerging. Here, we will initially review the canonical ligand‐induced EGFR signaling pathway, with particular emphasis to its regulation by endocytosis and subversion in human tumors. We will then focus on the most recent advances in uncovering noncanonical EGFR functions in stress‐induced trafficking, autophagy, and energy metabolism, with a perspective on future therapeutic applications.
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              Tumour evolution in hepatocellular carcinoma

              Hepatocellular carcinoma (HCC), the most common form of primary liver cancer, typically develops on the background of chronic liver disease and is an aggressive disease with dismal prognosis. Studies using next-generation sequencing of multiple regions of the same tumour nodule suggest different patterns of HCC evolution and confirm the high molecular heterogeneity in a subset of patients. Different hypotheses have been proposed to explain tumour evolution, including clonal selection or neutral and punctuated acquisition of genetic alterations. In parallel, data indicate a fundamental contribution of nonmalignant cells of the tumour microenvironment to cancer clonal evolution. Delineating these dynamics is crucial to improve the treatment of patients with HCC, and particularly to help understand how HCC evolution drives resistance to systemic therapies. A number of new minimally invasive techniques, such as liquid biopsies, could help track cancer evolution in HCC. These tools might improve our understanding of how systemic therapies affect tumour clonal composition and could facilitate implementation of real-time molecular monitoring of patients with HCC.
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                Author and article information

                Contributors
                (View ORCID Profile)
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                Journal
                Oncogene
                Oncogene
                Springer Science and Business Media LLC
                0950-9232
                1476-5594
                January 12 2023
                November 17 2022
                January 12 2023
                : 42
                : 3
                : 169-183
                Article
                10.1038/s41388-022-02545-x
                36385375
                044d1ddc-474a-4341-9772-4901140b7a2a
                © 2023

                https://www.springernature.com/gp/researchers/text-and-data-mining

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